The increasingly intelligent, highly complex, technical systems of tomorrow - for instance autonomous vehicles - result in the necessity for a systematic security- and safety-oriented development process that starts in the early phases of system design. Automotive Systems Engineering (ASE) as one approach is increasingly gaining ground in the automotive industry. However, this approach is still in a prototype stage. The consideration of security and safety within the early stages of systems design leads to so- called ill-defined problems. Such are not covered by ASE, but can be addressed by means of Design Thinking. Therefore we introduce an approach to combine both approaches. Based on this combination, we derive potentials in the context of the consideration of security and safety. Essential advantages are the possibility to think ahead of threat scenarios at an early stage in system design. Due to an incomplete database, this is not supported or only partially supported by conventional approaches. The resulting potentials are derived based upon a practical example.

Deep learning (DL) from various representations have succeeded in many fields. However, we know little about the machine learnability of distinct design representations when using DL to predict design performance. This paper proposes a graph representation for designs and compares it to the common image representation. We employ graph neural networks (GNNs) and convolutional neural networks (CNNs) respectively to learn them to predict drone performance. GCNs outperform CNNs by 2.6-8.1% in predictive validity. We argue that graph learning is a powerful and generalizable method for such tasks.

The control shifting between a human driver and a semi-autonomous vehicle is one of the most critical scenarios in the road-map of autonomous vehicle development. This paper proposes a methodology to study driver's behaviour in semi-autonomous driving with physiological-sensors-integrated driving simulators. A virtual scenario simulating take-over tasks has been implemented. The behavioural profile of the driver has been defined analysing key metrics collected by the simulator namely lateral position, steering wheel angle, throttle time, brake time, speed, and the take-over time. In addition, heart rate and skin conductance changes have been considered as physiological indicators to assess cognitive workload and reactivity. The methodology has been applied in an experimental study which results are crucial for taking insights on users’ behaviour. Results show that individual different driving styles and performance are able to be distinguished by calculating and elaborating the data collected by the system. This research provides potential directions for establishing a method to characterize a driver's behaviour in a semi-autonomous vehicle.

Customer survey data is critical to supporting customer preference modeling in engineering design. We present a framework of information retrieval and survey design to ensure the collection of quality customer survey data for analyzing customers’ preferences in their consideration-then-choice decision-making and the related social impact. The utility of our approach is demonstrated through the survey design for customers in the vacuum cleaner market. Based on the data, we performed descriptive analysis and network-based modeling to understand customers’ preferences in consideration and choice.

This study user-tested different data visualizations for highly uncertain life cycle assessments (LCAs) to determine what best supported decision-making. Precise LCAs can only be performed once designs are finalized, due to the information necessary to complete them, but design changes in such late stages are costly. If designers could have environmental impact data earlier in the process, sustainable design choices could instead be built into the initial designs. We compiled LCAs for various product categories, finding the best means of visualizing the data for online and printable dissemination. Because this LCA data varied widely within each product category, it was necessary to display uncertainty and require users to acknowledge the uncertainty. Here, four different data visualizations were tested with engineering, design, and STEM students and professionals; both quantitative and qualitative analysis determined what visualizations were most favored and forced users to consider uncertainty. We hope that this research helps LCA data be more accessible to designers and engineers in the early phases of design, allowing those without the resources or ability to perform LCA to benefit from it and design more sustainably.

Additive Manufacturing (AM) enables innovative product designs. One promising research field is AM of integrated electrically structures, e.g. heating panels using Joule effect. A mayor challenge in designing heating panels using AM is the dependency of its resultant resistivity from material, process and geometry parameters. The goal-oriented design of heating panels with individual surface temperatures the interactions between these parameters need to be understand. Therefore, a data-driven design approach is developed that facilitates a design of heating panels with specific properties.

Littering is a highly diffused anti-environmental and anti-social behavior, especially among young people. Furthermore, cigarette butts are one of the most littered items and are responsible for both severe environmental damages and high clean up expenses. The aim of this project is to design an interactive ashtray for the campus environment to limit the cigarette butts littering behavior in an engaging and effective way. Qualitative and quantitative data are collected. Coded observations were implemented through the research process, including the 2 pre (without the prototype) and 2 pros (with the prototype) sessions. Also, user experience test and one to one interview were conducted for deepening the understanding of the littering phenomenon and the reasons behind in the behavior among young people. The prototype indeed reduced the number of cigarette butts littering among observed behaviors of 156 students, especially in male sample. Final results indicate the behavior change of disposers is moderated by other factors, as the environmental cleanliness. Future development is also discussed.

Systems thinking is vital for engineering of nowadays systems characterized by system spanning interactions and an incresing amount of functions. Systems Engineering (SE) represents an interdisciplinary approach, gaining extensive attention to cope with increasing system complexity. Implementation of SE in existing organizations and processes, however, is facing challenges. As a matter of course there is not out of the box concept to be used, in fact definitions and understandings seem to be based on the background and experience of the individual or organization und differ widely. Thus, motivations and expectations of practitioner are manifold and support to adapte and implement SE-methodolgies is needed. Research presented in this contribution picks up the need to provide orientation for individuals, engineering teams and project managers when implementing SE and to address the specific context in that engineering is carried out. Objective is to describe the core idea of SE by a consistent set of principles. This set is used to build up a context specific understanding of SE as a foundation to introduce new methods and procedures in existing method ecosystems.

Technology of 3D printing is opening the possibility for small-scale production in quantities between ten and several hundred pieces. The technology of adding material enables the production of complex and integrated functional concepts in a single-pass process, which consequently potentially reduces the need for assembly operations. Design approaches and manufacturing processing are not mastered well because of a constant stream of new materials and manufacturing options. Well-designed products need to consider attributes of 3D printing as early as the conceptual phase. The cost of the product can be reduced with a systematic research and considering principles for small-scale production. In a cheaper, alternative production process the quality range of products is often lower. It has to be compensated with appropriate construction solutions which are less tolerance-sensitive. Therefore, in order to support the designer, to reduce the costs and design time of the product, a computer program was created to provide the user with an insight into the appropriate 3D printing technology. For simplifying the use, the program is also integrated into the product development process.

Purposeful qualitative modelling of embodiment function relations is a challenge in embodiment design. This contribution investigates the applicability and usefulness of the Contact and Channel Approach as a qualitative modelling approach in a survey study. From 23 development and research projects, advantages and challenges regarding applicability and usefulness are identified. A further result is that many different models are used additionally to the Contact and Channel Approach. Based on the findings, research potential for optimization and development of links to other models emerges.

Many research students find challenges when validating their research. Especially when they have expectations to contribute to both practice and the research body of knowledge. This paper argues that a key to successful validation of design research lies in the ability to focus on what to validate in advance of how to validate. The paper provide a set of guidelines to support a discussion on how to converge to a claim that actually can be validated. The paper reports on experiences from PhD level course on validation in design research.

Aluminum foam sandwich (AFS) is an innovative material combination for designing lighter products and has many advantages such as a high bending stiffness at a low density and good energy absorption properties. Although the material is ready for series production, the number of industrial applications is low because of the high costs of the material, a lack of design knowledge and missing reference applications. This paper focuses on the aspect of missing reference applications and how to improve this situation in order to give designers an idea of where the material could be used profitably and to provide the basis for a selection method. Therefore, a systematic literature review is carried out to identify profitable applications with their respective advantages. As a main result, a set of motivators for the use of aluminum foam sandwich is developed, which will support the designer in evaluating the potential use of aluminum foam sandwich.

The formalization of environmental issues has gained prominence since the definition of sustainable development by the Brundtland's report. Environmental performance has then been introduced to qualify the “green” contribution of an organization to its surrounding environment. However, its multi-dimensional aspects can be problematic when designing projects and making decisions, especially in the infrastructure sector where industrial activities are the most polluting ones. The aim of the study is to fill the environmental gap and confusion for decision-makers on the understanding of environmental performance, as well as to communicate on it, to define and share a clear vision and targets. A literature review is conducted and confronted with an industrial example in the railway sector to analyze the existing misunderstandings in industries while approaching environmental issues. By proposing and setting a clear framework of environmental performance, this research contributes to the conceptualization of environmental performance. More precisely, it characterizes an environmentally performant design project, in order to consider environmental performance as a driver and catalyzer of value creation.

The paper describes the rigorous implementation of a validated methodological experimental protocol to divergent and convergent thinking tasks occurring in Design by neurophysiological means (EEG and eye-tracking). EEG evidence confirms the findings coherently to the literature. Interesting is the confirmation of such results through eye-tracking ones, and further evidence emerged. In particular, neurophysiological results in idea generation differ between designers and engineers. This study was supported by a multidisciplinary team, both for the neuropsychological and data analysis aspects.

This paper suggests that analysing the effect of visualisation technologies during design reviews should include variables related to design reviewers’ expertise and focus on the process variables rather than the outcomes. The experiment showed better averages in terms of design understanding for groups in desktop interface than for groups in virtual reality. However, the observed difference might also be due to experience with the technology. Finally, regardless of the visualisation technology, higher expertise group showed consistently better design understanding than lower expertise groups.

For a company it is necessary to know, which products can be configured using carry-over-parts or the same technology. This can become quite relevant in the context of automobile electrification, where complex mechatronic systems are used. Consisting of various mechanical components, these systems perform the required function while being actuated by electronically controlled motors. To solve this, a novel mechanism for data driven portfolio analysis based on product platforms using knowledge-based systems is proposed in this paper. Further, the mechanism is tested by applying it to an electrical motors' case study. Using this method, all possible combinations of a product platform are calculated and finally displayed in different product portfolios. Additionally, all the non-feasible motor designs are removed from the solutions portfolio using the acquired knowledge base and performing design checks. The latter are employed for penalising and eliminating from the pareto-front of the designs, which violate the thermal, mechanical and acoustic constraints. The generated product portfolio can be used further to expand the systems engineering collaboration and support decision-making.

Human designers often work in a visual design space, projecting step-by-step design progression through evolving mental images. The strategic evolution of that design leverages heuristics based on experience and domain knowledge. The methodology presented in this paper brings together the visual nature of design problem solving and design heuristics in a deep learning computational agent framework that emulates and enables human-mirrored design. When applied to a truss design task, results demonstrate superior results to those of human designers who provided the initial data.

Requirements act as a limitation of the solution space, which represents the stakeholders’ needs and guides the whole product development process. Therefore, forgotten requirements can lead to wrong decisions when using them as a basis for decision-making. This contribution introduces a novel approach to link the requirement and evaluation criteria models to address this problem. For setting up those criteria consistently, the requirements are classified using natural language processing and derived by a ruleset based on a developed mapping between requirement classes and criteria types.

Crowdfunding is the process of taking a project in need of investment and asking a large group of people to supply the investment. It allows organisations to sell their product before production, reducing the risk of new product development. Organisations such as Tesla and General Electric have used crowdfunding successfully but crowdfunding is yet to be explored as part of a formalised product development framework. This paper includes the business case for commercialising new products with crowdfunding and presents crowdfunding as part of a product development and commercialisation framework.

With industries striving towards increased customisation of complex products through engineer-to-order, methods are continuously sought to rationalise the product development process. To this end, a framework is proposed using CAD configurators, utilising design automation and knowledge-based engineering to integrate sales and design processes in product development. The application of this framework to the design of spiral staircases is described and analysed, with results showing decreased lead-times and a decreased risk for design errors.